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In order to investigate the effects of process parameters on the quality of laser cladding layer, Co-based alloy laser cladding experiments based on orthogonal method was performed on the 304 stainless steel by high power diode laser (HPDL). The results show that the laser scanning speed has the most significant influence on the width, height and depth of laser cladding layer, and the powder feeding rate has the most important influence on the hardness of laser cladding layer. For the sake of getting optimum process parameters and reducing the times of process experiments in practical engineering application, a back propagation (BP) neural network model was established to predict the optimum process parameters. The calculation and predication results show a good agreement with the experimental results. The research results have both significant reference value and guidance meaning in processing parameters of Co-based alloy cladding by a high power diode laser in the application.

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